Energy storage capacity configuration and investment benefit evaluation method for high-proportion wind power

Abstract

The invention discloses an energy storage capacity configuration and investment benefit evaluation method for high-proportion wind power, and relates to the technical field of wind power management.The method includes the steps that a wind power twinborn scene is constructed, a plurality of wind power target objects are selected in the wind power twinborn scene for state analysis, and corresponding power configuration nodes are established based on the state analysis result; all power configuration nodes are integrated to build a power flow network, energy storage capacity configuration is carried out among a plurality of wind power target objects based on the power flow network, topology modeling is carried out on the configuration process of the energy storage capacity configuration, then a corresponding capacity interaction topological graph is built, real-time interaction data are obtained according to the capacity interaction topological graph, and the real-time interaction data are stored in the power flow network. Based on the real-time interaction data of each wind power target object on the capacity interaction topological graph, single investment benefits of the corresponding wind power target objects are obtained through evaluation, the single investment benefits of all the wind power target objects are integrated, and the overall investment benefits are obtained.

Description

Technical Field

[0001] This invention relates to the field of wind power management technology, specifically to a method for configuring energy storage capacity and evaluating investment benefits for high-proportion wind power. Background Technology

[0002] With a high proportion of wind power being integrated into the grid, the volatility and uncertainty of its output pose challenges to the stable operation of the system. Energy storage systems are a key means to improve the wind power absorption capacity; however, existing energy storage configuration and evaluation methods still have significant limitations. On the one hand, the configuration process often focuses on a single wind farm or local unit, lacking a systematic consideration of the synergistic and complementary capabilities among multiple wind power units across the entire farm, resulting in low configuration efficiency and high costs. On the other hand, benefit assessments mostly rely on static scenarios and hypothetical data, failing to integrate real-time operating status and system interaction relationships, making it difficult to accurately reflect the dynamic value of energy storage.

[0003] Furthermore, although digital twin technology has seen initial applications, it is mostly used for visualization and has not yet been deeply integrated with power flow and topology modeling, limiting its effectiveness in energy storage optimization and accurate evaluation. Therefore, there is an urgent need for a methodology that can connect the entire process from scenario construction to system evaluation to improve the scientific rigor of energy storage configuration and the reliability of investment returns. Summary of the Invention

[0004] The purpose of this invention is to provide a method for configuring energy storage capacity and evaluating investment benefits for high-proportion wind power, so as to solve the problems in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power, comprising the following steps: Step S1: Construct a wind power twin scenario, select several wind power target objects in the wind power twin scenario for state analysis, and establish corresponding power configuration nodes based on the results of the state analysis. Integrate all power configuration nodes to build a power transfer network. Step S2: Configure energy storage capacity among several wind power target objects based on the power transfer network, perform topology modeling on the configuration process of energy storage capacity, and then construct the corresponding capacity interaction topology diagram. Obtain real-time interaction data based on the capacity interaction topology diagram. Step S3: Based on the real-time interactive data of each wind power target object on the capacity interaction topology map, evaluate the individual investment benefits of the corresponding wind power target object, and conduct a comprehensive evaluation of all wind power target objects to obtain the overall investment benefits.

[0006] In a preferred embodiment, the process of constructing a wind power twin scenario includes: Obtain the physical structure and physical state of wind power equipment and energy grid in several locations within a wind farm, and use the physical structure and physical state as scene elements and element attributes of scene elements, respectively. Deploy a scene rendering engine in each location area to generate a virtual framework of the scene structure for that location area, and process all scene elements in the same location area into filling elements of the virtual framework of the scene structure using digital twin technology. The filling elements are mapped to the virtual framework of the scene structure based on their distribution location in the wind farm, and the sub-twin scene corresponding to the current location area is constructed. The sub-twin scenes corresponding to all locations of the wind farm are spliced ​​together to construct the wind power twin scene corresponding to the entire wind farm.

[0007] In a preferred embodiment, the process of selecting several wind power target objects for state analysis in a wind power twin scenario includes: Each scene element is treated as a wind power target object. A status tracking node is set for each wind power target object. A monitoring period is created, and the wind power-related data of the wind power target object under the monitoring period is imported into the corresponding status tracking node. The status tracking node splits wind power-related data into several sub-stage data packets based on timestamps, and compares each sub-stage data packet with preset standard reference data. When the comparison results are consistent, the object status under the corresponding timestamp is marked as normal; otherwise, the object status under the corresponding timestamp is marked as abnormal. By integrating the object status of the same wind power target object at different timestamps, the global status of the corresponding wind power target object within the monitoring period is obtained. If the number of timestamps in the normal state exceeds the number of timestamps in the abnormal state within the monitoring period, the global status is marked as normal; otherwise, the global status is marked as abnormal.

[0008] In a preferred embodiment, the process of establishing corresponding power configuration nodes based on the results of state analysis and integrating all power configuration nodes to build a power transfer network includes: When the global state of a certain wind power target object is abnormal, a main power configuration node and a branch power configuration node are established for the corresponding wind power target object. When the global state of a certain wind power target object is normal, only the main power configuration node is established for the wind power target object. An object data domain is generated for the power configuration node of each wind power target object. A flow path is established between two adjacent wind power target objects. The main power configuration node of each wind power target object is attached to the flow path. When a wind power target object has both a main power configuration node and a branch power configuration node, a data communication path is built between the main power configuration node and the branch power configuration node. When the power configuration node of each wind power target object is successfully attached to the transfer path, a power energy storage grid is created synchronously for each wind power target object, and data sharing is carried out between the power energy storage grid and the power configuration node. The power energy storage grid of all power configuration nodes is integrated to build the power transfer network of the entire wind power twin scenario.

[0009] In a preferred embodiment, the process of configuring energy storage capacity among several wind power targets based on the power transfer network includes: Two power configuration nodes connected to the same flow path are selected as a power flow combination. Several power flow combinations on the power flow network are traversed, and the power energy storage grids of the power configuration nodes corresponding to each power flow combination are connected to obtain the total grid storage capacity of each power flow combination after connecting all power energy storage grids. Set a first reserve threshold and a second reserve threshold; When the total grid storage of a certain power transfer group is not greater than the first storage threshold, it initiates an energy storage configuration application to other power transfer groups. After receiving the configuration application, other power transfer groups determine whether their own wind power energy storage can support the current energy storage configuration. If so, the corresponding power transfer combination will be used as the energy storage supply object or the backup energy storage supply object. Specifically, when the total grid storage of the power transfer combination is between the first storage threshold and the second storage threshold, the power transfer combination will be used as the backup energy storage supply object, and wind power energy storage will be distributed to the power transfer combination that initiated the energy storage configuration application through the transfer path. If not, no operation will be performed until the overall wind power energy storage in the entire wind power twin scenario is balanced and then the energy storage capacity configuration will be stopped.

[0010] In a preferred embodiment, the configuration process of energy storage capacity configuration is topologically modeled to construct a corresponding capacity interaction topology diagram. The process of obtaining real-time interaction data based on the capacity interaction topology diagram includes: Each power configuration node is treated as a topology object. A topology edge is constructed between two adjacent topology objects. The capacity interaction direction, capacity interaction value, and capacity interaction type of the power configuration nodes represented by the two topology objects are marked on the topology edge. Each topology object's sub-topology stage is constructed and its state is marked. All interaction data items of each topology object in each sub-topology stage during the configuration process are obtained. A topology region subgraph of the scene area where each two topology objects are located is constructed. All topology region subgraphs in the entire wind power twin scenario are spliced ​​together to obtain the final capacity interaction topology map. The capacity interaction topology map is used to record the real-time interaction data of several adjacent wind power target objects during the energy storage capacity configuration process.

[0011] In a preferred embodiment, the process of constructing sub-topology phases for each topology object and marking their states, and obtaining all interactive data items for each sub-topology phase of each topology object during the configuration process, includes: The topology execution time of two topology objects during energy storage capacity configuration and until completion is obtained. The entire configuration process of the two topology objects is decomposed into several sub-topology stages by setting a unit monitoring time. Based on the topology execution time, unit monitoring time, and capacity interaction value, the unit topology interaction value corresponding to any sub-topology stage is obtained. The unit topology interaction value is as follows: ; Obtain the actual topology interaction value when configuring the energy storage capacity between two topology objects in each sub-topology stage, obtain the initial blank structure diagram based on the scene architecture of the entire wind power twin scenario, map each topology object to the corresponding position on the initial blank structure diagram based on its position in the wind power twin scenario, and build its own interaction component for each topology object. The interactive components include a first display axis and a second display axis. The first display axis arranges and displays the unit topology interaction values ​​of the same topology object in different sub-topology stages in chronological order. The second display axis arranges and displays the actual topology interaction values ​​of the same topology object in different sub-topology stages in chronological order. The unit topology interaction value and actual topology interaction value of each topology object in the same sub-topology stage on the first and second display axes are integrated as the interaction data item of the topology object in the current sub-topology stage. When the unit topology interaction value and actual topology interaction value in the interaction data item are not within the preset topology difference range, the corresponding sub-topology stage is marked as an abnormal sub-stage; otherwise, it is marked as a normal sub-stage.

[0012] In a preferred embodiment, the process of evaluating the individual investment benefits of each wind power target based on real-time interaction data on the capacity interaction topology map, and then comprehensively evaluating all wind power target objects to obtain the overall investment benefits includes: Construct a baseline scenario corresponding to the current wind power twin scenario; Import the real-time interaction data of each wind power target object on the capacity interaction topology map into the scenario baseline scenario, compare and analyze the value benefit difference between each wind power target object in the actual scenario scenario and the scenario baseline scenario, and obtain the corresponding scenario operation time of each wind power target object in the wind power twin scenario. The scenario baseline scenario corresponds to the recording of scenario baseline interaction data. The scenario baseline interaction data and the real-time interaction data of each wind power target object on the capacity interaction topology map are processed by a pre-built bag-of-words model to obtain the scenario similarity between the actual scenario and the scenario baseline scenario. The scenario similarity is used as the value benefit difference between the actual scenario and the scenario baseline scenario. The investment efficiency rate of each wind power target object in the wind power twin scenario is obtained based on the value-benefit difference and the scenario operation time. The investment efficiency rate of the wind power target object is used to characterize the individual investment efficiency of the wind power target object. The average rate of return on investment for all wind power targets is taken as the scenario investment efficiency corresponding to the entire wind power twin scenario. The scenario investment efficiency is then evaluated as the overall investment efficiency of all wind power targets under the entire wind power twin scenario.

[0013] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention constructs a wind power twin scenario and integrates power configuration nodes to form a power transfer network, realizing the interconnection and interoperability of all wind power objects and the coordinated scheduling of energy storage resources, improving the utilization efficiency of energy storage capacity, performing topology modeling of the energy storage configuration process, generating a capacity interaction topology diagram and acquiring real-time interaction data, making the configuration process highly transparent and traceable, evaluating the individual investment benefits of each wind power target object based on real-time interaction data, and comprehensively obtaining the overall investment benefits, realizing a comprehensive quantitative evaluation from local units to the entire system, providing accurate basis for investment decisions and operational optimization. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0015] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1, please refer to Figure 1As shown in this embodiment, the method for configuring energy storage capacity and evaluating investment benefits for high-proportion wind power includes the following steps: Step S1: Construct a wind power twin scenario, select several wind power target objects in the wind power twin scenario for state analysis, and establish corresponding power configuration nodes based on the results of the state analysis. Integrate all power configuration nodes to build a power transfer network. Step S2: Configure energy storage capacity among several wind power target objects based on the power transfer network, perform topology modeling on the configuration process of energy storage capacity, and then construct the corresponding capacity interaction topology diagram. Obtain real-time interaction data based on the capacity interaction topology diagram. Step S3: Based on the real-time interactive data of each wind power target object on the capacity interaction topology map, evaluate the individual investment benefits of the corresponding wind power target object, and conduct a comprehensive evaluation of all wind power target objects to obtain the overall investment benefits.

[0018] It should be further explained that, in the specific implementation process, the process of constructing a wind power twin scenario and selecting several wind power target objects for state analysis within the wind power twin scenario includes: Obtain the scene construction drawings corresponding to the wind farm. The scene construction drawings are used to record the physical structure and physical state of wind power equipment and energy grid in several locations and areas of the wind farm. Each physical structure is treated as a scene element, and the physical state of the corresponding physical structure is treated as the element attribute of the scene element. Deploy a scene rendering engine in each location area, generate a virtual frame of scene structure corresponding to the current location area through the scene rendering engine, and process all scene elements in the same location area into filling elements corresponding to the virtual frame of scene structure through digital twin technology. The filling elements are mapped to the virtual framework of the scene structure based on their corresponding distribution positions in the wind farm, thereby constructing the sub-twin scene corresponding to the current location area. The sub-twin scenes corresponding to all locations of the wind farm are spliced ​​together to construct the wind power twin scene corresponding to the entire wind farm. Each scene element in the wind power twin scenario is selected as a wind power target object in turn to obtain several wind power target objects. A state tracking node is set for each wind power target object, a monitoring period is created, and the wind power-related data of the wind power target object under the monitoring period is imported into the corresponding state tracking node. The status tracking node splits wind power-related data into several sub-stage data packets based on timestamps, and compares each sub-stage data packet with preset standard reference data. When the comparison results are consistent, the object status under the corresponding timestamp is marked as normal; otherwise, the object status under the corresponding timestamp is marked as abnormal. The object status of the same wind power target object at different timestamps is integrated to obtain the global status of the corresponding wind power target object within the monitoring period. If the number of timestamps in the normal state exceeds the number of timestamps in the abnormal state within the monitoring period, the global status is marked as normal; otherwise, the global status is marked as abnormal.

[0019] It should be further explained that, in the specific implementation process, the process of establishing corresponding power configuration nodes based on the results of state analysis and integrating all power configuration nodes to build a power transfer network includes: Obtain the results of all target wind power objects after completing the state analysis, and select to establish different types of power configuration nodes based on the results and complete the configuration. When the result of the state analysis of a certain wind power target object is that the global state is abnormal, establish a main power configuration node and a branch power configuration node for the corresponding wind power target object. When the result of the state analysis of a certain wind power target object is that the global state is normal, only establish a main power configuration node for the corresponding wind power target object. For each wind power target object, a corresponding object data domain is generated for the power configuration node. The object data domain includes a basic attribute domain, a status evaluation domain, an operating parameter domain, and a configuration parameter domain. The basic attribute field includes node identifier, node geographical coordinates, rated installed capacity and node equipment type; the status evaluation field is used to characterize the global status, power output fluctuation index and real-time power output index of the power configuration node; the operation parameter field includes the predicted power output curve and historical wind curtailment rate of the wind power configuration node; and the configuration parameter field includes the maximum allowable energy storage capacity and the maximum allowable energy storage power of the wind power configuration node. Establish a flow path between adjacent wind power target objects at every two locations, and attach the main power configuration node of each wind power target object to the flow path. When a wind power target object has both a main power configuration node and a branch power configuration node, construct a data communication path between the main power configuration node and the branch power configuration node. When the power configuration node of each wind power target object is successfully attached to the transfer path, a power energy storage grid is created synchronously for each wind power target object, and data sharing is carried out between the power energy storage grid and the power configuration node. The power energy storage grids corresponding to all power configuration nodes are integrated, thereby completing the power transfer network in the entire wind power twin scenario.

[0020] It should be further explained that, in the specific implementation process, the process of configuring energy storage capacity among several wind power targets based on the power transfer network includes: Two power configuration nodes connected to the same power transfer path in the power transfer network are selected as a power transfer combination. The power transfer network is traversed to obtain several power transfer combinations on the power transfer network. Connect the power storage grids of the power configuration nodes corresponding to each power transfer combination, obtain the total grid storage capacity of each power transfer combination after connecting all power storage grids, and set a first storage threshold and a second storage threshold. Several power flow combinations are labeled, and the labels are denoted as follows: Then there is =1, 2, 3, ..., n, where n is a natural number greater than 0, labeled as The total grid storage corresponding to the power flow combination is denoted as The first and second reserve thresholds are respectively denoted as... as well as , where 0 < < ; When a certain power flow combination exists ≤ When the wind power is in use, it will initiate an energy storage configuration application to other power transfer groups on the power transfer network. The other power transfer groups will receive the configuration application and determine whether their own wind power energy storage can support the current energy storage configuration. When the total grid storage corresponding to the power transfer combination receiving the configuration request is greater than the second storage threshold, it is determined that the corresponding power transfer combination can support this energy storage configuration, and the power transfer combination is used as the energy storage supply object. When the total grid storage is between the first storage threshold and the second storage threshold, the power transfer combination is used as the backup energy storage supply object. When the total grid storage is less than or equal to the first storage threshold, no operation is performed on the corresponding power transfer combination. The wind power energy storage corresponding to the energy storage supply object is distributed to the power transfer combination that initiated the energy storage configuration application through the power transfer network, thereby completing the energy storage supply at the location where wind power energy storage is insufficient. When the wind power energy storage at each power transfer combination meets the requirement of being greater than the first storage threshold, it indicates that the overall wind power energy storage in the current wind power twin scenario is in balance.

[0021] It should be further explained that, in the specific implementation process, the configuration process of energy storage capacity configuration involves topology modeling, thereby constructing a corresponding capacity interaction topology diagram. The process of obtaining real-time interaction data based on the capacity interaction topology diagram includes: Each power configuration node on the power transfer network is treated as a topology object. A topology edge is constructed between two adjacent topology objects. The capacity interaction direction, capacity interaction value, and capacity interaction type of the power configuration nodes represented by the two topology objects are marked on the topology edge. The capacity interaction direction includes both positive and negative directions; When a topological object in a preceding position transfers its own wind power storage to another topological object connected through a topological edge, it represents a positive direction of capacity interaction; otherwise, it represents a negative direction of capacity interaction. Obtain the start and end timestamps of two topology objects for energy storage capacity configuration until the end, and obtain the topology execution duration of the two topology objects by subtracting the start and end timestamps. Set the unit monitoring duration. Based on the unit monitoring duration, the entire configuration process of the two topology objects is decomposed into several sub-topology stages. Based on the topology execution duration, unit monitoring duration, and capacity interaction value, the unit topology interaction value corresponding to any sub-topology stage is obtained. The unit topology interaction value is described as follows: ; Obtain the actual topology interaction value corresponding to the energy storage capacity configuration between two topology objects in each sub-topology stage. The actual topology interaction value represents the actual capacity of wind power energy storage interaction between the two topology objects in the corresponding sub-topology stage. Based on the scene architecture of the entire wind power twin scenario, an initial blank structure diagram is constructed. Each topology object is mapped to the corresponding position on the initial blank structure diagram based on its position in the wind power twin scenario, and a corresponding interactive component is constructed for each topology object. The interactive component includes a first display axis and a second display axis; The first display axis is used to arrange and display the unit topology interaction values ​​of the same topology object in different sub-topology stages in chronological order; The second display axis is used to arrange and display the actual topology interaction values ​​of the same topology object in different sub-topology stages in chronological order; For each topology object, the unit topology interaction value and the actual topology interaction value of the topology object in the same sub-topology stage on the first display axis and the second display axis are integrated and then used as the interaction data item of the topology object in the current sub-topology stage. When the unit topology interaction value and the actual topology interaction value in the interaction data item are not within the preset topology difference range, the corresponding sub-topology stage is marked as an abnormal sub-stage; otherwise, the corresponding sub-topology stage is marked as a normal sub-stage. Integrate all interaction data items corresponding to several sub-topology stages during the configuration process of each pair of topology objects that are configuring energy storage capacity, and then use them as the interaction dataset of the two topology objects in the energy storage capacity configuration process. Based on the interaction dataset, construct the topology sub-graph of the scene area where the two topology objects are located, and stitch together all the topology sub-graphs in the entire wind power twin scenario to obtain the final capacity interaction topology graph. The capacity interaction topology map is used to record the real-time interaction data of several adjacent wind power target objects during the energy storage capacity configuration process. The real-time interaction data is used to characterize all the interaction records of wind power energy storage during the interaction process between two wind power target objects.

[0022] It should be further explained that, in the specific implementation process, the individual investment benefits of each wind power target are evaluated based on the real-time interaction data of each wind power target on the capacity interaction topology map. The process of comprehensively evaluating all wind power target targets to obtain the overall investment benefits includes: Construct a baseline scenario corresponding to the current wind power twin scenario. The baseline scenario is used to characterize the wind power energy storage operation status of the wind power target object at each location area in the wind power twin scenario. The wind power energy storage operation status represents the value and benefits held by the current wind power target object in the entire wind farm. Import the real-time interaction data of each wind power target object on the capacity interaction topology map into the scenario baseline scenario, and then compare and analyze to obtain the value benefit difference between each wind power target object in the actual scenario scenario and the scenario baseline scenario, and obtain the corresponding scenario operation time of each wind power target object in the wind power twin scenario. The scenario operation time is the total time for the wind power target object to carry out wind power energy storage related work in the wind power twin scenario. The scenario benchmark scenario records the scenario benchmark interaction data. The scenario benchmark interaction data and the real-time interaction data of each wind power target object on the capacity interaction topology map are processed by the pre-built bag-of-words model to obtain the scenario similarity between the actual scenario and the scenario benchmark scenario. The scenario similarity is used as the value benefit difference between the actual scenario and the scenario benchmark scenario. The investment return rate (ROR) of each wind power target object in the wind power twin scenario is obtained based on the value-benefit difference and the scenario operation time. The RRO = Value-benefit difference ÷ Scenario operation time × 100%. The RRO represents the individual investment benefit of each wind power target object; a higher RRO indicates higher individual investment benefit, and vice versa. The average rate of return on investment for all wind power targets is taken as the scenario investment efficiency corresponding to the entire wind power twin scenario. The scenario investment efficiency is then evaluated as the overall investment efficiency of all wind power targets under the entire wind power twin scenario.

[0023] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for configuring energy storage capacity and evaluating investment benefits for high-proportion wind power, characterized in that, Includes the following steps: Step S1: Construct a wind power twin scenario, select several wind power target objects in the wind power twin scenario for state analysis, and establish corresponding power configuration nodes based on the results of the state analysis. Integrate all power configuration nodes to build a power transfer network. Step S2: Configure energy storage capacity among several wind power target objects based on the power transfer network, perform topology modeling on the configuration process of energy storage capacity, and then construct the corresponding capacity interaction topology diagram. Obtain real-time interaction data based on the capacity interaction topology diagram. Step S3: Based on the real-time interactive data of each wind power target object on the capacity interaction topology map, evaluate the individual investment benefits of the corresponding wind power target object, and conduct a comprehensive evaluation of all wind power target objects to obtain the overall investment benefits.

2. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 1, characterized in that, The process of building a wind power twin scenario includes: Obtain the physical structure and physical state of wind power equipment and energy grid in several locations within a wind farm, and use the physical structure and physical state as scene elements and element attributes of scene elements, respectively. Deploy a scene rendering engine in each location area to generate a virtual framework of the scene structure for that location area, and process all scene elements in the same location area into filling elements of the virtual framework of the scene structure using digital twin technology. The filling elements are mapped to the virtual framework of the scene structure based on their distribution location in the wind farm, and the sub-twin scene corresponding to the current location area is constructed. The sub-twin scenes corresponding to all locations of the wind farm are spliced ​​together to construct the wind power twin scene corresponding to the entire wind farm.

3. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 2, characterized in that, The process of selecting several wind power target objects for state analysis in a wind power twin scenario includes: Each scene element is treated as a wind power target object. A status tracking node is set for each wind power target object. A monitoring period is created, and the wind power-related data of the wind power target object under the monitoring period is imported into the corresponding status tracking node. The status tracking node splits wind power-related data into several sub-stage data packets based on timestamps, and compares each sub-stage data packet with preset standard reference data. When the comparison results are consistent, the object status under the corresponding timestamp is marked as normal; otherwise, the object status under the corresponding timestamp is marked as abnormal. By integrating the object status of the same wind power target object at different timestamps, the global status of the corresponding wind power target object within the monitoring period is obtained. If the number of timestamps in the normal state exceeds the number of timestamps in the abnormal state within the monitoring period, the global status is marked as normal; otherwise, the global status is marked as abnormal.

4. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 3, characterized in that, The process of establishing corresponding power configuration nodes based on the results of state analysis and integrating all power configuration nodes to build a power transfer network includes: When the global state of a certain wind power target object is abnormal, a main power configuration node and a branch power configuration node are established for the corresponding wind power target object. When the global state of a certain wind power target object is normal, only the main power configuration node is established for the wind power target object. An object data domain is generated for the power configuration node of each wind power target object. A flow path is established between two adjacent wind power target objects. The main power configuration node of each wind power target object is attached to the flow path. When a wind power target object has both a main power configuration node and a branch power configuration node, a data communication path is built between the main power configuration node and the branch power configuration node. When the power configuration node of each wind power target object is successfully attached to the transfer path, a power energy storage grid is created synchronously for each wind power target object, and data sharing is carried out between the power energy storage grid and the power configuration node. The power energy storage grid of all power configuration nodes is integrated to build the power transfer network of the entire wind power twin scenario.

5. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 4, characterized in that, The process of configuring energy storage capacity among several wind power targets based on the power grid includes: Two power configuration nodes connected to the same flow path are selected as a power flow combination. Several power flow combinations on the power flow network are traversed, and the power energy storage grids of the power configuration nodes corresponding to each power flow combination are connected to obtain the total grid storage capacity of each power flow combination after connecting all power energy storage grids. Set a first reserve threshold and a second reserve threshold; When the total grid storage of a certain power transfer group is not greater than the first storage threshold, it initiates an energy storage configuration application to other power transfer groups. After receiving the configuration application, other power transfer groups determine whether their own wind power energy storage can support the current energy storage configuration. If so, the corresponding power transfer combination will be used as the energy storage supply object or the backup energy storage supply object. Specifically, when the total grid storage of the power transfer combination is between the first storage threshold and the second storage threshold, the power transfer combination will be used as the backup energy storage supply object, and wind power energy storage will be distributed to the power transfer combination that initiated the energy storage configuration application through the transfer path. If not, no operation will be performed until the overall wind power energy storage in the entire wind power twin scenario is balanced and then the energy storage capacity configuration will be stopped.

6. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 5, characterized in that, The process of configuring energy storage capacity involves topology modeling to construct a corresponding capacity interaction topology diagram, and obtaining real-time interaction data based on this diagram. Each power configuration node is treated as a topology object. A topology edge is constructed between two adjacent topology objects. The capacity interaction direction, capacity interaction value, and capacity interaction type of the power configuration nodes represented by the two topology objects are marked on the topology edge. Each topology object's sub-topology stage is constructed and its state is marked. All interaction data items of each topology object in each sub-topology stage during the configuration process are obtained. A topology region subgraph of the scene area where each two topology objects are located is constructed. All topology region subgraphs in the entire wind power twin scenario are spliced ​​together to obtain the final capacity interaction topology map. The capacity interaction topology map is used to record the real-time interaction data of several adjacent wind power target objects during the energy storage capacity configuration process.

7. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 6, characterized in that, The process of constructing sub-topology phases for each topology object and marking their states, and obtaining all interaction data items for each sub-topology phase during the configuration process of each topology object includes: The topology execution time of two topology objects during energy storage capacity configuration and until completion is obtained. The entire configuration process of the two topology objects is decomposed into several sub-topology stages by setting a unit monitoring time. Based on the topology execution time, unit monitoring time, and capacity interaction value, the unit topology interaction value corresponding to any sub-topology stage is obtained. The unit topology interaction value is as follows: ； Obtain the actual topology interaction value when configuring the energy storage capacity between two topology objects in each sub-topology stage, obtain the initial blank structure diagram based on the scene architecture of the entire wind power twin scenario, map each topology object to the corresponding position on the initial blank structure diagram based on its position in the wind power twin scenario, and build its own interaction component for each topology object. The interactive components include a first display axis and a second display axis. The first display axis arranges and displays the unit topology interaction values ​​of the same topology object in different sub-topology stages in chronological order. The second display axis arranges and displays the actual topology interaction values ​​of the same topology object in different sub-topology stages in chronological order. The unit topology interaction value and actual topology interaction value of each topology object in the same sub-topology stage on the first and second display axes are integrated as the interaction data item of the topology object in the current sub-topology stage. When the unit topology interaction value and actual topology interaction value in the interaction data item are not within the preset topology difference range, the corresponding sub-topology stage is marked as an abnormal sub-stage; otherwise, it is marked as a normal sub-stage.

8. The method for energy storage capacity configuration and investment benefit evaluation for high-proportion wind power as described in claim 7, characterized in that, Based on the real-time interaction data of each wind power target on the capacity interaction topology map, the individual investment benefits of the corresponding wind power target are evaluated. The process of comprehensively evaluating all wind power target targets to obtain the overall investment benefits includes: Construct a baseline scenario corresponding to the current wind power twin scenario; Import the real-time interaction data of each wind power target object on the capacity interaction topology map into the scenario baseline scenario, compare and analyze the value benefit difference between each wind power target object in the actual scenario scenario and the scenario baseline scenario, and obtain the corresponding scenario operation time of each wind power target object in the wind power twin scenario. The scenario baseline scenario corresponds to the recording of scenario baseline interaction data. The scenario baseline interaction data and the real-time interaction data of each wind power target object on the capacity interaction topology map are processed by a pre-built bag-of-words model to obtain the scenario similarity between the actual scenario and the scenario baseline scenario. The scenario similarity is used as the value benefit difference between the actual scenario and the scenario baseline scenario. The investment efficiency rate of each wind power target object in the wind power twin scenario is obtained based on the value-benefit difference and the scenario operation time. The investment efficiency rate of the wind power target object is used to characterize the individual investment efficiency of the wind power target object. The average rate of return on investment for all wind power targets is taken as the scenario investment efficiency corresponding to the entire wind power twin scenario. The scenario investment efficiency is then evaluated as the overall investment efficiency of all wind power targets under the entire wind power twin scenario.

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